code: def test_not_enough_components():
      s = (
          "Number of principal components must match the number"
          " of eigenvalues. Got 2 != 1"
      )
      with pytest.raises(ValueError, match=s):
          X, y = iris_data()
          pca = PCA(n_components=2)
          X_pca = pca.fit_transform(X)
          eigen = pca.explained_variance_
  
          plot_pca_correlation_graph(
              X,
              variables_names=["1", "2", "3", "4"],
              X_pca=X_pca,
              explained_variance=eigen[:-1],
          )
  
file_path: mlxtend/mlxtend/plotting/tests/test_pca_corr_graph.py
imports: import pytest
  from packaging.version import Version
  from sklearn import __version__
  from mlxtend.data import iris_data
  from mlxtend.plotting import plot_pca_correlation_graph
label_desc: Use image node_id 5 for calling a global function with example usage: test_not_enough_components() without return types